Fault Tolerance Analysis and Self-Healing Strategy of Autonomous, Evolvable Hardware Systems

This paper presents an analysis of the fault tolerance achieved by an autonomous, fully embedded evolvable hardware system, which uses a combination of partial dynamic reconfiguration and an evolutionary algorithm (EA). It demonstrates that the system may self-recover from both transient and cumulative permanent faults. This self-adaptive system, based on a 2D array of 16 (4×4) Processing Elements (PEs), is tested with an image filtering application. Results show that it may properly recover from faults in up to 3 PEs, that is, more than 18% cumulative permanent faults. Two fault models are used for testing purposes, at PE and CLB levels. Two self-healing strategies are also introduced, depending on whether fault diagnosis is available or not. They are based on scrubbing, fitness evaluation, dynamic partial reconfiguration and in-system evolutionary adaptation. Since most of these adaptability features are already available on the system for its normal operation, resource cost for self-healing is very low (only some code additions in the internal microprocessor core)

Soliton's eigenvalue based analysis on the generation mechanism of rogue wave phenomenon in optical fibers exhibiting weak third order dispersion

One of the extraordinary aspects of nonlinear wave evolution which has been observed as the spontaneous occurrence of astonishing and statistically extraordinary amplitude wave is called rogue wave. We show that the eigenvalues of the associated equation of nonlinear Schrödinger equation are almost constant in the vicinity of rogue wave and we validate that optical rogue waves are formed by the collision between quasi-solitons in anomalous dispersion fiber exhibiting weak third order dispersion.

Uma investigação das sequências de fase Hebbianas descritas como grafos de assembleias neuronais

Hebb proposed that synapses between neurons that fire synchronously are strengthened, forming cell assemblies and phase sequences. The former, on a shorter scale, are ensembles of synchronized cells that function transiently as a closed processing system; the latter, on a larger scale, correspond to the sequential activation of cell assemblies able to represent percepts and behaviors. Nowadays, the recording of large neuronal populations allows for the detection of multiple cell assemblies. Within Hebb’s theory, the next logical step is the analysis of phase sequences. Here we detected phase sequences as consecutive assembly activation patterns, and then analyzed their graph attributes in relation to behavior. We investigated action potentials recorded from the adult rat hippocampus and neocortex before, during and after novel object exploration (experimental periods). Within assembly graphs, each assembly corresponded to a node, and each edge corresponded to the temporal sequence of consecutive node activations. The sum of all assembly activations was proportional to firing rates, but the activity of individual assemblies was not. Assembly repertoire was stable across experimental periods, suggesting that novel experience does not create new assemblies in the adult rat. Assembly graph attributes, on the other hand, varied significantly across behavioral states and experimental periods, and were separable enough to correctly classify experimental periods (Naïve Bayes classifier; maximum AUROCs ranging from 0.55 to 0.99) and behavioral states (waking, slow wave sleep, and rapid eye movement sleep; maximum AUROCs ranging from 0.64 to 0.98). Our findings agree with Hebb’s view that neuronal assemblies correspond to primitive building blocks of representation, nearly unchanged in 10 the adult, while phase sequences are labile across behavioral states and change after novel experience. The results are compatible with a role for phase sequences in behavior and cognition

Global slowing of network oscillations in mouse neocortex by diazepam

SCHEFFZUK, C. , KUKUSHKA, V. , VYSSOTSKI, A. L. , DRAGUHN, A. , TORT, A. B. L. , BRANKACK, J. . Global slowing of network oscillations in mouse neocortex by diazepam. Neuropharmacology , v. 65, p. 123-133, 2013.

An investigation of Hebbian phase sequences as assembly graphs

Hebb proposed that synapses between neurons that fire synchronously are strengthened, forming cell assemblies and phase sequences. The former, on a shorter scale, are ensembles of synchronized cells that function transiently as a closed processing system; the latter, on a larger scale, correspond to the sequential activation of cell assemblies able to represent percepts and behaviors. Nowadays, the recording of large neuronal populations allows for the detection of multiple cell assemblies. Within Hebb's theory, the next logical step is the analysis of phase sequences. Here we detected phase sequences as consecutive assembly activation patterns, and then analyzed their graph attributes in relation to behavior. We investigated action potentials recorded from the adult rat hippocampus and neocortex before, during and after novel object exploration (experimental periods). Within assembly graphs, each assembly corresponded to a node, and each edge corresponded to the temporal sequence of consecutive node activations. The sum of all assembly activations was proportional to firing rates, but the activity of individual assemblies was not. Assembly repertoire was stable across experimental periods, suggesting that novel experience does not create new assemblies in the adult rat. Assembly graph attributes, on the other hand, varied significantly across behavioral states and experimental periods, and were separable enough to correctly classify experimental periods (Naïve Bayes classifier; maximum AUROCs ranging from 0.55 to 0.99) and behavioral states (waking, slow wave sleep, and rapid eye movement sleep; maximum AUROCs ranging from 0.64 to 0.98). Our findings agree with Hebb's view that assemblies correspond to primitive building blocks of representation, nearly unchanged in the adult, while phase sequences are labile across behavioral states and change after novel experience. The results are compatible with a role for phase sequences in behavior and cognition.

Global slowing of network oscillations in mouse neocortex by diazepam

SCHEFFZUK, C. , KUKUSHKA, V. , VYSSOTSKI, A. L. , DRAGUHN, A. , TORT, A. B. L. , BRANKACK, J. . Global slowing of network oscillations in mouse neocortex by diazepam. Neuropharmacology , v. 65, p. 123-133, 2013.

An investigation of Hebbian phase sequences as assembly graphs

Hebb proposed that synapses between neurons that fire synchronously are strengthened, forming cell assemblies and phase sequences. The former, on a shorter scale, are ensembles of synchronized cells that function transiently as a closed processing system; the latter, on a larger scale, correspond to the sequential activation of cell assemblies able to represent percepts and behaviors. Nowadays, the recording of large neuronal populations allows for the detection of multiple cell assemblies. Within Hebb's theory, the next logical step is the analysis of phase sequences. Here we detected phase sequences as consecutive assembly activation patterns, and then analyzed their graph attributes in relation to behavior. We investigated action potentials recorded from the adult rat hippocampus and neocortex before, during and after novel object exploration (experimental periods). Within assembly graphs, each assembly corresponded to a node, and each edge corresponded to the temporal sequence of consecutive node activations. The sum of all assembly activations was proportional to firing rates, but the activity of individual assemblies was not. Assembly repertoire was stable across experimental periods, suggesting that novel experience does not create new assemblies in the adult rat. Assembly graph attributes, on the other hand, varied significantly across behavioral states and experimental periods, and were separable enough to correctly classify experimental periods (Naïve Bayes classifier; maximum AUROCs ranging from 0.55 to 0.99) and behavioral states (waking, slow wave sleep, and rapid eye movement sleep; maximum AUROCs ranging from 0.64 to 0.98). Our findings agree with Hebb's view that assemblies correspond to primitive building blocks of representation, nearly unchanged in the adult, while phase sequences are labile across behavioral states and change after novel experience. The results are compatible with a role for phase sequences in behavior and cognition.

Effects of the length and timing of nighttime naps on task performance and physiological function

OBJECTIVE: To examine the effects of the length and timing of nighttime naps on performance and physiological functions, an experimental study was carried out under simulated night shift schedules. METHODS: Six students were recruited for this study that was composed of 5 experiments. Each experiment involved 3 consecutive days with one night shift (22:00-8:00) followed by daytime sleep and night sleep. The experiments had 5 conditions in which the length and timing of naps were manipulated: 0:00-1:00 (E60), 0:00-2:00 (E120), 4:00-5:00 (L60), 4:00-6:00 (L120), and no nap (No-nap). During the night shifts, participants underwent performance tests. A questionnaire on subjective fatigue and a critical flicker fusion frequency test were administered after the performance tests. Heart rate variability and rectal temperature were recorded continuously during the experiments. Polysomnography was also recorded during the nap. RESULTS: Sleep latency was shorter and sleep efficiency was higher in the nap in L60 and L120 than that in E60 and E120. Slow wave sleep in the naps in E120 and L120 was longer than that in E60 and L60. The mean reaction time in L60 became longer after the nap, and faster in E60 and E120. Earlier naps serve to counteract the decrement in performance and physiological functions during night shifts. Performance was somewhat improved by taking a 2-hour nap later in the shift, but deteriorated after a one-hour nap. CONCLUSIONS: Naps in the latter half of the night shift were superior to earlier naps in terms of sleep quality. However performance declined after a 1-hour nap taken later in the night shift due to sleep inertia. This study suggests that appropriate timing of a short nap must be carefully considered, such as a 60-min nap during the night shift.

Modeling resting-state functional networks when the cortex falls asleep: local and global changes.

The transition from wakefulness to sleep represents the most conspicuous change in behavior and the level of consciousness occurring in the healthy brain. It is accompanied by similarly conspicuous changes in neural dynamics, traditionally exemplified by the change from "desynchronized" electroencephalogram activity in wake to globally synchronized slow wave activity of early sleep. However, unit and local field recordings indicate that the transition is more gradual than it might appear: On one hand, local slow waves already appear during wake; on the other hand, slow sleep waves are only rarely global. Studies with functional magnetic resonance imaging also reveal changes in resting-state functional connectivity (FC) between wake and slow wave sleep. However, it remains unclear how resting-state networks may change during this transition period. Here, we employ large-scale modeling of the human cortico-cortical anatomical connectivity to evaluate changes in resting-state FC when the model "falls asleep" due to the progressive decrease in arousal-promoting neuromodulation. When cholinergic neuromodulation is parametrically decreased, local slow waves appear, while the overall organization of resting-state networks does not change. Furthermore, we show that these local slow waves are structured macroscopically in networks that resemble the resting-state networks. In contrast, when the neuromodulator decrease further to very low levels, slow waves become global and resting-state networks merge into a single undifferentiated, broadly synchronized network.

Electroencephalogram paroxysmal theta characterizes cataplexy in mice and children.

Astute control of brain activity states is critical for adaptive behaviours and survival. In mammals and birds, electroencephalographic recordings reveal alternating states of wakefulness, slow wave sleep and paradoxical sleep (or rapid eye movement sleep). This control is profoundly impaired in narcolepsy with cataplexy, a disease resulting from the loss of orexin/hypocretin neurotransmitter signalling in the brain. Narcolepsy with cataplexy is characterized by irresistible bouts of sleep during the day, sleep fragmentation during the night and episodes of cataplexy, a sudden loss of muscle tone while awake and experiencing emotions. The neural mechanisms underlying cataplexy are unknown, but commonly thought to involve those of rapid eye movement-sleep atonia, and cataplexy typically is considered as a rapid eye movement sleep disorder. Here we reassess cataplexy in hypocretin (Hcrt, also known as orexin) gene knockout mice. Using a novel video/electroencephalogram double-blind scoring method, we show that cataplexy is not a state per se, as believed previously, but a dynamic, multi-phased process involving a reproducible progression of states. A knockout-specific state and a stereotypical paroxysmal event were introduced to account for signals and electroencephalogram spectral characteristics not seen in wild-type littermates. Cataplexy almost invariably started with a brief phase of wake-like electroencephalogram, followed by a phase featuring high-amplitude irregular theta oscillations, defining an activity profile distinct from paradoxical sleep, referred to as cataplexy-associated state and in the course of which 1.5-2 s high-amplitude, highly regular, hypersynchronous paroxysmal theta bursts (∼7 Hz) occurred. In contrast to cataplexy onset, exit from cataplexy did not show a predictable sequence of activities. Altogether, these data contradict the hypothesis that cataplexy is a state similar to paradoxical sleep, even if long cataplexies may evolve into paradoxical sleep. Although not exclusive to overt cataplexy, cataplexy-associated state and hypersynchronous paroxysmal theta activities are highly enriched during cataplexy in hypocretin/orexin knockout mice. Their occurrence in an independent narcolepsy mouse model, the orexin/ataxin 3 transgenic mouse, undergoing loss of orexin neurons, was confirmed. Importantly, we document for the first time similar paroxysmal theta hypersynchronies (∼4 Hz) during cataplexy in narcoleptic children. Lastly, we show by deep recordings in mice that the cataplexy-associated state and hypersynchronous paroxysmal theta activities are independent of hippocampal theta and involve the frontal cortex. Cataplexy hypersynchronous paroxysmal theta bursts may represent medial prefrontal activity, associated in humans and rodents with reward-driven motor impulse, planning and conflict monitoring.

Sustained sleep fragmentation induces sleep homeostasis in mice.

STUDY OBJECTIVES: Sleep fragmentation (SF) is an integral feature of sleep apnea and other prevalent sleep disorders. Although the effect of repetitive arousals on cognitive performance is well documented, the effects of long-term SF on electroencephalography (EEG) and molecular markers of sleep homeostasis remain poorly investigated. To address this question, we developed a mouse model of chronic SF and characterized its effect on EEG spectral frequencies and the expression of genes previously linked to sleep homeostasis including clock genes, heat shock proteins, and plasticity-related genes. DESIGN: N/A. SETTING: Animal sleep research laboratory. PARTICIPANTS: Sixty-six C57BL6/J adult mice. INTERVENTIONS: Instrumental sleep disruption at a rate of 60/h during 14 days. MEASUREMENTS AND RESULTS: Locomotor activity and EEG were recorded during 14 days of SF followed by recovery for 2 days. Despite a dramatic number of arousals and decreased sleep bout duration, SF minimally reduced total quantity of sleep and did not significantly alter its circadian distribution. Spectral analysis during SF revealed a homeostatic drive for slow wave activity (SWA; 1-4 Hz) and other frequencies as well (4-40 Hz). Recordings during recovery revealed slow wave sleep consolidation and a transient rebound in SWA, and paradoxical sleep duration. The expression of selected genes was not induced following chronic SF. CONCLUSIONS: Chronic SF increased sleep pressure confirming that altered quality with preserved quantity triggers core sleep homeostasis mechanisms. However, it did not induce the expression of genes induced by sleep loss, suggesting that these molecular pathways are not sustainably activated in chronic diseases involving SF.

Étude de l’implication de la Neuroligine 1 dans le processus homéostatique de régulation du sommeil chez la souris

Le sommeil est essentiel au bon fonctionnement de l’organisme. Ce dernier est régulé, entre autres, par le processus de régulation homéostatique qui dépend de la pression de sommeil accumulée suite à l’éveil. Des études ont suggéré que ce processus pourrait être lié à la plasticité synaptique, et que le changement de la pression de sommeil affecterait le degré de plasticité du cerveau. Les récepteurs N-méthyl-D-aspartate, des médiateurs importants de plasticité, semblent impliqués dans les conséquences délétères du manque de sommeil ainsi que dans la régulation de la synchronisation corticale caractéristique du sommeil lent profond. Leur activité est contrôlée par Neuroligine 1 (NLGN1), une molécule d’adhésion synaptique. Une mutation de Nlgn1 a des effets similaires à ceux de la privation de sommeil sur la mémoire et le comportement. Dans le manuscrit de mon mémoire, nous présentons l’hypothèse d’une implication de NLGN1 dans la régulation du sommeil et de l’éveil. Pour tester cette hypothèse, l’expression d’ARNm et de protéine NLGN1 a été mesurée suite à une privation de sommeil et le sommeil de souris n’exprimant pas NLGN1 a été caractérisé. Les résultats de mon projet de maîtrise montrent, en premier lieu, qu’une augmentation de la pression pour dormir altère l’expression de l’ARNm et de la protéine NLGN1 chez la souris. De plus, nos observations révèlent qu’une mutation de Nlgn1 diminue la quantité d’éveil et modifie l’activité spectrale en éveil et en sommeil. Ces observations dévoilent l’importance de NLGN1 dans le maintien de l’éveil et la régulation du sommeil, et supportent un rôle de NLGN1 dans la régulation de l’activité neuronale.

Endothelial function and sleep: associations of flow-mediated dilation with perceived sleep quality and rapid eye movement (REM) sleep.

Endothelial function typically precedes clinical manifestations of cardiovascular disease and provides a potential mechanism for the associations observed between cardiovascular disease and sleep quality. This study examined how subjective and objective indicators of sleep quality relate to endothelial function, as measured by brachial artery flow-mediated dilation (FMD). In a clinical research centre, 100 non-shift working adults (mean age: 36 years) completed FMD testing and the Pittsburgh Sleep Quality Index, along with a polysomnography assessment to obtain the following measures: slow wave sleep, percentage rapid eye movement (REM) sleep, REM sleep latency, total arousal index, total sleep time, wake after sleep onset, sleep efficiency and apnea-hypopnea index. Bivariate correlations and follow-up multiple regressions examined how FMD related to subjective (i.e., Pittsburgh Sleep Quality Index scores) and objective (i.e., polysomnography-derived) indicators of sleep quality. After FMD showed bivariate correlations with Pittsburgh Sleep Quality Index scores, percentage REM sleep and REM latency, further examination with separate regression models indicated that these associations remained significant after adjustments for sex, age, race, hypertension, body mass index, apnea-hypopnea index, smoking and income (Ps < 0.05). Specifically, as FMD decreased, scores on the Pittsburgh Sleep Quality Index increased (indicating decreased subjective sleep quality) and percentage REM sleep decreased, while REM sleep latency increased (Ps < 0.05). Poorer subjective sleep quality and adverse changes in REM sleep were associated with diminished vasodilation, which could link sleep disturbances to cardiovascular disease.

Random Sampling with Interspike-Intervals of the Exponential Integrate and Fire Neuron: A Computational Interpretation of UP-States

Oscillations between high and low values of the membrane potential (UP and DOWN states respectively) are an ubiquitous feature of cortical neurons during slow wave sleep and anesthesia. Nevertheless, a surprisingly small number of quantitative studies have been conducted only that deal with this phenomenon’s implications for computation. Here we present a novel theory that explains on a detailed mathematical level the computational benefits of UP states. The theory is based on random sampling by means of interspike intervals (ISIs) of the exponential integrate and fire (EIF) model neuron, such that each spike is considered a sample, whose analog value corresponds to the spike’s preceding ISI. As we show, the EIF’s exponential sodium current, that kicks in when balancing a noisy membrane potential around values close to the firing threshold, leads to a particularly simple, approximative relationship between the neuron’s ISI distribution and input current. Approximation quality depends on the frequency spectrum of the current and is improved upon increasing the voltage baseline towards threshold. Thus, the conceptually simpler leaky integrate and fire neuron that is missing such an additional current boost performs consistently worse than the EIF and does not improve when voltage baseline is increased. For the EIF in contrast, the presented mechanism is particularly effective in the high-conductance regime, which is a hallmark feature of UP-states. Our theoretical results are confirmed by accompanying simulations, which were conducted for input currents of varying spectral composition. Moreover, we provide analytical estimations of the range of ISI distributions the EIF neuron can sample from at a given approximation level. Such samples may be considered by any algorithmic procedure that is based on random sampling, such as Markov Chain Monte Carlo or message-passing methods. Finally, we explain how spike-based random sampling relates to existing computational theories about UP states during slow wave sleep and present possible extensions of the model in the context of spike-frequency adaptation.